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While in a classification or a regression setting a label or a value is assigned to each individual document, in a ranking setting we determine the relevance ordering of the entire input document list.
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Learning to rank for information retrieval
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A Neural Click Model for Web Search. In Proc. of the 25th International Conference on World Wide Web . 531–541
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Learning to Diversify Search Results via Subtopic Attention. In Proc. of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval . 545–554
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Unbiased Learning-to-Rank with Biased Feedback. In Proc. of the 10th ACM International Conference on Web Search and Data Mining . 781–789
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Learning to Match Using Local and Distributed Representations of Text for Web Search. In Proc. of the 26th International Conference on World Wide Web . 1291–1299
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DeepRank: A New Deep Architecture for Relevance Ranking in Information Retrieval. In Proc. of the 2017 ACM Conference on Information and Knowledge Management . 257–266
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Situational Context for Ranking in Personal Search. In Proc. of the 26th International Conference on World Wide Web . 1531–1540
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Learning a deep listwise context model for ranking refinement. In The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval . ACM, 135–144
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